Introduction to Operations ResearchCD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |
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Page 225
... given information to identify the optimal solution . ( b ) Use the given information to identify the shadow prices for the three resources . Z ( 0 ) 1 1 1 0 X2 ( 1 ) 0 1 3 0 X6 ( 2 ) 0 0 1 1 X3 ( 3 ) 0 1 2 0 1 5.2-2 . * Work through the ...
... given information to identify the optimal solution . ( b ) Use the given information to identify the shadow prices for the three resources . Z ( 0 ) 1 1 1 0 X2 ( 1 ) 0 1 3 0 X6 ( 2 ) 0 0 1 1 X3 ( 3 ) 0 1 2 0 1 5.2-2 . * Work through the ...
Page 786
... Given that the research is not done , use Bayes ' decision rule to determine which decision alternative should be chosen . T ( b ) Find EVPI . Does this answer indicate that it might be worthwhile to do the research ? ( c ) Given that ...
... Given that the research is not done , use Bayes ' decision rule to determine which decision alternative should be chosen . T ( b ) Find EVPI . Does this answer indicate that it might be worthwhile to do the research ? ( c ) Given that ...
Page 1187
... given win 0.45 win and win lose , given win 0.25 0.15 win and lose 0.818 win , given win 0.333 win , given lose Lose 0.4 0.25 win , given lose 0.1 lose and win 0.182 lose , given win lose , given lose 0.75 0.3 lose and lose 0.667 lose , ...
... given win 0.45 win and win lose , given win 0.25 0.15 win and lose 0.818 win , given win 0.333 win , given lose Lose 0.4 0.25 win , given lose 0.1 lose and win 0.182 lose , given win lose , given lose 0.75 0.3 lose and lose 0.667 lose , ...
Other editions - View all
Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost Courseware CPLEX decision variables described dual problem dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau flow following problem formulation functional constraints Gaussian elimination given graphical identify increase initial BF solution integer iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize Z maximum flow problem Minimize needed node nonbasic variables nonnegativity constraints objective function obtained optimal solution optimality test parameters path plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero